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cs.CV2018★ 3 cited
Diverse Image-to-Image Translation via Disentangled Representations
Hsin-Ying Lee, Hung-Yu Tseng, Jia-Bin Huang +2
Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for many applications: 1) the lack of aligned training pairs and 2) m…
cs.LG2018★ 51 cited
Disconnected Manifold Learning for Generative Adversarial Networks
Mahyar Khayatkhoei, Ahmed Elgammal, Maneesh Singh
Natural images may lie on a union of disjoint manifolds rather than one globally connected manifold, and this can cause several difficulties for the training of common Generative A…
cs.CV2018★ 9 cited
Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders
Ananya Harsh Jha, Saket Anand, Maneesh Singh +1
Generative models that learn disentangled representations for different factors of variation in an image can be very useful for targeted data augmentation. By sampling from the dis…